136 lines
6.3 KiB
Python
136 lines
6.3 KiB
Python
import sys
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import os
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import asyncio
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from textwrap import dedent
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from pathlib import Path
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from datetime import datetime
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import streamlit as st
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from gtts import gTTS
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import base64
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv(Path('../../.env'))
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# Logger setup
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from loguru import logger
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logger.remove()
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logger.add(sys.stdout,
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colorize=True,
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format="<level>{level}</level>|<green>{file}:{line}:{function}</green>| {message}")
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# Import other necessary modules
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from ..ai_web_researcher.gpt_online_researcher import (
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do_google_serp_search, do_tavily_ai_search,
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do_metaphor_ai_research, do_google_pytrends_analysis)
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from .blog_from_google_serp import write_blog_google_serp, blog_with_research
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from ..ai_web_researcher.you_web_reseacher import get_rag_results, search_ydc_index
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from ..blog_metadata.get_blog_metadata import blog_metadata
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from ..blog_postprocessing.save_blog_to_file import save_blog_to_file
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from ..gpt_providers.text_to_image_generation.main_generate_image_from_prompt import generate_image
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# Function to convert text to speech and save as an audio file
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def text_to_speech(text, lang='en'):
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tts = gTTS(text=text, lang=lang)
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tts.save("output.mp3")
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return "output.mp3"
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# Function to get audio file as a downloadable link
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def get_audio_file(audio_file):
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with open(audio_file, "rb") as file:
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data = file.read()
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b64_data = base64.b64encode(data).decode()
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return f'<a href="data:audio/mp3;base64,{b64_data}" download="output.mp3">Download audio file</a>'
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def write_blog_from_keywords(search_keywords, url=None):
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"""
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This function will take a blog Topic to first generate sections for it
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and then generate content for each section.
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"""
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# Use to store the blog in a string, to save in a *.md file.
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blog_markdown_str = None
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tavily_search_result = None
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example_blog_titles = []
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logger.info(f"Researching and Writing Blog on keywords: {search_keywords}")
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with st.status("Started Writing..", expanded=True) as status:
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st.empty()
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status.update(label="Researching and Writing Blog on keywords.")
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# Call on the got-researcher, tavily apis for this. Do google search for organic competition.
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try:
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google_search_result, g_titles = do_google_serp_search(search_keywords)
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status.update(label=f"🙎 Finished with Google web for Search: {search_keywords}")
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example_blog_titles.append(g_titles)
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status.update(label=f"🛀 Starting Tavily AI research: {search_keywords}")
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tavily_search_result, t_titles, t_answer = do_tavily_ai_search(search_keywords)
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status.update(label=f"🙆 Finished Google Search & Tavily AI Search on: {search_keywords}",
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state="complete", expanded=False)
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except Exception as err:
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st.error(f"Failed in web research: {err}")
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logger.error(f"Failed in web research: {err}")
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with st.status("Started Writing blog from google search..", expanded=True) as status:
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status.update(label="Researching and Writing Blog on keywords.")
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# Call on the got-researcher, tavily apis for this. Do google search for organic competition.
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try:
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status.update(label=f"🛀 Writing blog from Google Search on: {search_keywords}")
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blog_markdown_str = write_blog_google_serp(search_keywords, google_search_result)
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st.markdown(blog_markdown_str)
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status.update(label="🙎 Draft 1: Your Content from Google search result.", state="complete", expanded=False)
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except Exception as err:
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st.error(f"Failed in Google web research: {err}")
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logger.error(f"Failed in Google web research: {err}")
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# logger.info/check the final blog content.
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logger.info("######### Draft1: Finished Blog from Google web search: ###########")
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with st.status("Started Writing blog from Tavily Web search..", expanded=True) as status:
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# Do Tavily AI research to augment the above blog.
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try:
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# example_blog_titles.append(t_titles)
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if blog_markdown_str and tavily_search_result:
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logger.info(f"\n\n######### Blog content after Tavily AI research: ######### \n\n")
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blog_markdown_str = write_blog_google_serp(search_keywords, tavily_search_result)
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status.update(label=f"Finished Writing Blog From Tavily Results:{blog_markdown_str}", expanded=True)
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except Exception as err:
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logger.error(f"Failed to do Tavily AI research: {err}")
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status.update(label="🙎 Generating - Title, Meta Description, Tags, Categories for the content.", expanded=True)
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try:
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blog_title, blog_meta_desc, blog_tags, blog_categories = asyncio.run(blog_metadata(blog_markdown_str))
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except Exception as err:
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st.error(f"Failed to get blog metadata: {err}")
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generated_image_filepath = None
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try:
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# FIXME: Temporary fix.
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text_to_image = f"{blog_title} + ' ' + {blog_meta_desc}"
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if not text_to_image:
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text_to_image = blog_markdown_str
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generated_image_filepath = generate_image(text_to_image)
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except Exception as err:
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st.warning(f"Failed in Image generation: {err}")
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saved_blog_to_file = save_blog_to_file(blog_markdown_str, blog_title, blog_meta_desc,
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blog_tags, blog_categories, generated_image_filepath)
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status.update(label=f"Saved the content in this file: {saved_blog_to_file}")
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logger.info(f"\n\n --------- Finished writing Blog for : {search_keywords} -------------- \n")
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# Render the result on streamlit UI
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if generated_image_filepath:
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st.image(generated_image_filepath)
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st.markdown(f"{blog_markdown_str}")
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status.update(label=f"Finished, Review & Use your Original Content Below: {saved_blog_to_file}",
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state="complete")
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# Passing the text and language to the engine, here we have marked slow=False. Which tells
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# the module that the converted audio should have a high speed
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tts = gTTS(text=blog_markdown_str, lang='en', slow=False)
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# Saving the converted audio in a mp3 file
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tts.save("delete_me.mp3")
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st.audio("delete_me.mp3")
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